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Multiomics analysis reveals a distinct response mechanism in multiple primary lung adenocarcinoma after neoadjuvant immunotherapy.

ABSTRACT: Multiple primary lung cancer (MPLC) remains a tough challenge to diagnose and treat. Although neoadjuvant immunotherapy has shown promising results in early stage non-small cell lung cancer, whether such modality can benefit all primary lesions remains unclear. Herein, we performed integrated multiomics analysis in one patient with early stage MPLC with remarkable tumor shrinkage in a solid nodule and no response in two subsolid nodules after treatment with three cycles of neoadjuvant pembrolizumab. Genomic heterogeneity was observed among responding nodules with high levels of infiltrating CD8⁺ and CD68⁺ immune cells. Substantially downregulated human leukocyte antigen (HLA)-related genes and impaired T lymphocyte function were observed in non-responding nodules. A larger proportion of infiltrating tissue resident memory T cells (Trm) along with high T cell receptor repertoire clonality in responding nodules were validated as predictive and prognostic biomarkers in multiple cancer types using external public datasets. These results suggested that neoadjuvant programmed death 1 (PD-1)/programmed death ligand 1 inhibitors alone may not be an optimal therapeutic strategy for MPLC due to disparities in genomic alterations and immune microenvironment among different lesions. Additionally, we postulate that increased infiltration of Trm may be a unique marker of early immune responses to PD-1 blockade.

SUBMITTER: Zhang C

PROVIDER: S-EPMC8025811 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Lung adenocarcinoma has entered into an era of immunotherapy with the development of immune checkpoint inhibitors (ICIs). The identification of immune subtype is crucial to prolonging survival in patients. The tumor microenvironment (TME) and metabolism have a profound impact on prognosis and therapy. The majority of previous studies focused on only one aspect, while both of them are essential to the understanding of tumorigenesis and development. We hypothesized that lung adenocarcinoma can be stratified into immune subgroups with alterations in the TME infiltration. We aimed to explore the "TME-Metabolism-Risk" patterns in each subtypes and the mechanism behind. Glycolysis and cholesterol were selected for the analysis of metabolic states based on the first half of the study. Bioinformatic analysis was performed to investigate the transcriptomic and clinical data integrated by three lung adenocarcinoma cohorts (GSE30219, GSE31210, GSE37745, N = 415). The results were validated in an independent cohort (GSE50081, N = 127). In total, 415 lung adenocarcinoma samples were integrated and analyzed. Four major immune subtypes were indentified using bioinformatic analysis. Subtype NC1, characterized by a high level of glycolysis, with extremely low microenvironment cell infiltration. Subtype NC2, characterized by the "Silence" and "Cholesterol biosynthesis Predominant" metabolic states, with a middle degree infiltration of microenvironment cell. Subtype NC3, characterized by the lack of "Cholesterol biosynthesis Predominant" metabolic state, with abundant microenvironment cell infiltration. Subtype NC4, characterized by "Mixed" metabolic state, with a relatively low microenvironment cell infiltration. Least absolute shrinkage and selection operator (LASSO) regression and multivariate analyses were performed to calculate the risk of each sample, and we attempted to find out the potential immune escape mechanism in different subtypes. The result revealed that the lack of immune cells infiltration might contribute to the immune escape in subtypes NC1 and NC4. NC3 was characterized by the high expression of immune checkpoint molecules and fibroblasts. NC2 had defects in activation of innate immune cells. There existed an obviously survival advantage in subtype NC2. Gene set enrichment analysis (GSEA) and Gene Ontology analysis indicated that the PI3K-AKT-mTOR, TGF-β, MYC-related pathways might be correlated with this phenomenon. In addition, some differentially expressed genes (DEGs) were indentified in subtype NC3, which might be potential targets for survival phenotype transformation.

Project description:IntroductionAcute ischemic stroke (AIS) and lung adenocarcinoma (LUAD) are associated with some of the highest morbidity and mortality rates worldwide. Despite reports on their strong correlation, the causal relationship is not fully understood. The study aimed to identify and annotate the biological functions of hub genes with clinical diagnostic efficacy in AIS and LUAD.MethodsTranscriptome and single-cell datasets were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). We identified the differentially expressed genes (DEGs) upregulated in AIS and LUAD and found 372 genes intersecting both datasets. Hub genes were identified using protein-protein interaction (PPI) networks, and the diagnostic and prognostic utility of these hub genes was then investigated using receiver operating characteristic (ROC) curves, survival analysis, and univariable Cox proportional hazard regression. Single-cell analysis was used to detect whether the hub genes were expressed in tumor epithelial cells. The immune microenvironment of AIS and LUAD was assessed using the CIBERSORT algorithm. The protein expression of these hub genes was tracked using the Human Protein Atlas (HPA). We calculated the number of positive cells using the digital pathology software QuPath. Finally, we performed molecular docking after using the Enrichr database to predict possible medicines.ResultsWe identified the molecular mechanisms underlying hub genes in AIS and LUAD and found that CCNA2, CCNB1, CDKN2A, and CDK1 were highly expressed in AIS and LUAD tissue samples compared to controls. The hub genes were mainly involved in the following pathways: the cell cycle, cellular senescence, and the HIF-1 signaling pathway. Using immunohistochemical slices from the HPA database, we confirmed that these hub genes have a high diagnostic capability for AIS and LUAD. Further, their high expression is associated with poor prognosis. Finally, curcumin was tested as a potential medication using molecular docking modeling.DiscussionOur findings suggest that the hub genes we found in this study contribute to the development and progression of AIS and LUAD by altering the cellular senescence pathway. Thus, they may be promising markers for diagnosis and prognosis.

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Multiomics analysis reveals a distinct response mechanism in multiple primary lung adenocarcinoma after neoadjuvant immunotherapy.

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